The background description provided herein is for the purpose of generally presenting the context of the disclosure. Work of the presently named inventors, to the extent it is described in this background section, as well as aspects of the description that may not otherwise qualify as prior art at the time of filing, are neither expressly nor impliedly admitted as prior art against the present disclosure.
Chronic obstructive pulmonary disease (COPD) is a highly and increasingly prevalent disorder referring to a group of lung diseases that block airflow during exhalation and make it increasingly difficult to breathe. COPD is one cause of morbidity, mortality, and healthcare cost worldwide with an estimated global prevalence of approximately 12% of adults aged ≥30 years in 2010 and rising with the ageing population. COPD can cause coughing that produces large amounts of mucus, wheezing, shortness of breath, chest tightness, and other symptoms. Emphysema and chronic asthmatic bronchitis are two of the main conditions that make up COPD. Cigarette smoking is one leading cause of COPD. Many people who have COPD smoke or used to smoke. Long-term exposure to other lung irritants, such as air pollution, chemical fumes, or dust, also may contribute to COPD. In all cases, damage to lung airways may eventually interfere with the exchange of oxygen and carbon dioxide in the lungs, which can lead to bodily injury. COPD is generally identified by airway limitations that may arise from progressive emphysematous lung destruction, small airways disease, or a combination of both. COPD is a heterogeneous disorder that can arise from pathological processes including emphysematous lung tissue destruction, gross airway disease, and functional small airways disease (fSAD) in varying combinations and severity within an individual patient. It is generally accepted that fSAD and emphysema are two main components of COPD and that a spectrum of COPD phenotypes with varying contributions of these two components exists in individual patients. Recent reports found that COPD etiology varies among populations, including risk factors associated with tobacco smoke, cooking fuels, environmental pollution and family genetics. This has led to the current understanding that COPD covers a spectrum of pathophysiologies.
Given the high prevalence and clinical cost of COPD, there is a need for further advancements to enable COPD phenotypes and therapy response to be quantified. Beyond COPD, small airway obstruction is a primary manifestation in various other lung diseases, including asthma, obliterative bronchiolitis, and cystic fibrosis. Venegas, J. G., et al. Self-organized patchiness in asthma can represent a prelude to catastrophic shifts. Nature 434, 777-782 (2005). Some have recently explored the importance of disease heterogeneity and local interaction between neighboring structures using model simulations of asthma. They have shown that small heterogeneity in ventilation potential produces an imbalance in the system leading to large patched effects, termed self-organized clustering.
Numerous techniques have been used in attempting to measure COPD, including several imaging techniques. Computer tomography (CT) is a minimally invasive imaging technique that is capable of providing both high contrast and detailed resolution of the pulmonary systems and that has been used to aid physicians in identifying structural abnormalities associated with COPD. Although CT is primarily used qualitatively (i.e., through visual inspection), research has been devoted to the application of quantitative CT, measured in Hounsfield Units (HU) for identifying underlying specific COPD phenotypes, with the hopes that such quantitative techniques would dictate an effective treatment strategy for the patient. Knowing the precise COPD phenotype for an individual patient, including the location, type, and severity of damage throughout the lungs would allow for the formulation of a tailored treatment regimen that accounts for the patient's specific disease state.
Clinical presentation and monitoring of COPD have been described primarily through spirometry as pulmonary function measurements, such as forced expiratory volume in one second (FEV1). Although highly reproducible, these measurements assess the lungs as a whole and are unable to differentiate two important components of COPD: emphysema and small airways disease. In addition, spirometry does not provide spatial context for regional heterogeneity of these components. X-ray computed tomography (CT) has addressed some of these limitations by allowing clinicians to verify emphysema in patients exhibiting loss of pulmonary function. Even with these techniques, COPD is often undiagnosed in early stages, impeding proper treatment with the disease potentially progressing to permanent lung damage (i.e. emphysema). Although COPD phenotyping has been prolifically reported in the literature, lack of accurate diagnostic tools have hampered the development of effective therapies. Nevertheless, significant advances in technologies are providing physicians opportunities to shift towards more effective, localized therapies.
Various strategies have been undertaken to identify metrics that more accurately assess COPD subtypes, such as genetic, molecular and cellular markers as well as medical imaging devices and methodologies. Although advances in biological phenotyping have shown promise in identifying disease heterogeneity in patients, these approaches are generally either global measures or highly invasive. In contrast, medical imaging provides clinicians with a relatively non-invasive and reproducible approach that provides functional information that is spatially defined.
A variety of CT-based metrics have been evaluated separately on inspiratory and expiratory CT scans or in combination. One metric that may be used is the lung relative volume of emphysema known as Low Attenuation Areas (LAA), which is determined by the sum of all image voxels with HU<−950 normalized to total inspiratory lung volume on a quantitative CT scan. This metric may be calculated using standard imaging protocols making it readily measurable at clinical sites for evaluation, and the LAA approach has been validated by pathology. However, this metric only identifies a portion of one component (i.e. emphysema) of the spectrum of underlying COPD phenotypes discussed above. Nevertheless, the validation of LAA has prompted researchers to investigate the utility of inspiratory and expiratory CT scans, either analyzed individually as with LAA or in unison, to identify imaging biomarkers that provide for a more accurate correlate of COPD.
Although various instruments (e.g. PET, SPECT and MRI) are heavily investigated as surrogates of clinical outcome, CT, with its high resolution and lung contrast, continues to be the most widely used medical imaging device in the clinic. As such, advances in this technology are likely to have an important impact on patient care. CT can be considered a quantitative map, where attenuation scans are approximated as linearly proportional to tissue density, represented as Hounsfield units (HU). Extensive research in CT image post-processing has generated an array of potentially diagnostic and prognostic measures. Filter-based techniques and airway wall measurements have been also been used. Although these methodologies have advanced understanding of COPD, many have found limited use in the clinic due to concerns about cost and radiation exposure. Nevertheless, the quantification of discrete phenotypes of emphysema using CT has had an impact on patient care. At present at least three emphysema patterns (i.e., centrilobular, panlobular, and paraseptal emphysema) have been identified, each of which are strongly associated with a range of respiratory physiologies and functional measures. The understanding that spatial patterns of emphysema serve as indicators of COPD subtypes has spawned progress in lobe segmentation algorithms as well as the need to evaluate topological features.